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- “Risk-aware machine learning systems for safety and quality-critical applications”. He/She will carry out research in the area of machine learning and data science, and also be required to: (a
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principled machine learning approaches inspired by geometry, physics, or domain constraints. Modelling latent representations of complex biological systems or medical imaging (e.g., genomic time series
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system design. We employ advanced computational methods, machine learning, modeling, and custom hardware and software to continually test our solutions in various real-world industry projects. In one
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organ-on-a-chip (OOC) models, colony picking and bioprinting). The ideal candidate should have strong expertise performing machine learning (ML), computational biology with the capability and/or
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research and model development for Artificial Intelligence, especially multi-agent systems and NLP. Experience in prototypes and intelligent tools development. Evidence of developing Machine Learning and
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cases. AI Model Development & Engineering: Design and implement machine learning models for specific business challenges. Optimize AI models through lightweight experimentation, rapid evaluation, and
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well as bulk RNA-Seq, Proteomics, and Metabolomics generated from mouse and patient cohorts with rich clinical data - Advanced modeling of arrhythmias using generalized linear models and machine learning
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R or equivalent skills in another relevant language. We are not expecting you to be an expert in all forms of computer simulation, Large Language Models, or machine learning etc, but a working
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, including high throughput experimentation to generate novel types of organic reaction datasets and the development of adapted machine learning models. This role is ideal for a Ph.D.-level scientist with
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Martin Australia invite applications for a project under this program, advancing robotic perception systems through monitoring of their machine learning models. Run-Time Monitoring of Machine Learning